The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. Here we describe the Synthetic Biology Open Language (SBOL), a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a communitydriven, formalized format for exchange between software tools, research groups and commercial service providers. The SBOL Developers Group has implemented SBOL as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. We describe early successes, including a demonstration of the utility of SBOL for information exchange between several different software tools and repositories from both academic and industrial partners. As a community-driven standard, SBOL will be updated as synthetic biology evolves to provide specific capabilities for different aspects of the synthetic biology workflow.Synthetic biology treats biological organisms as a new technological medium with a unique set of characteristics, such as the ability to self-repair, evolve and replicate. These characteristics create their own engineering challenges, but offer a rich and largely untapped source of potential applications across a broad range of sectors 1,2 . Applications such as biomolecular computing 3 , metabolic engineering 4 , or reconstruction and exploration of natural cell biology 5,6 commonly require the design of new genetically encoded systems. As engineers, synthetic biologists most often base their designs on previously described 'DNA segments' (see Supplementary Table 1 for definitions of selected terms) to meet their design requirements. Reuse of the DNA sequence for these segments involves their exchange between laboratories and their hierarchical composition to form devices and systems with higher level function.Every engineering field relies on a set of 'standards' 7 that practitioners follow to enable the exchange and reuse of designs for 'systems' , 'devices' and 'components' . Similarly, the representation of synthetic biology designs using computer-readable 'data standards' has the potential to facilitate the forward engineering of novel biological systems from previously characterized devices and components. For example, such standards could enable synthetic biology companies to offer catalogs of devices and components by means of computerreadable data sheets, just as modern semiconductor companies do for electronics. Such standards could also enable a synthetic biologist to develop portions of a design using one software tool, refine the design using another tool, and finally transmit it electronically to a colleague or commercial fabrication company.In order for synthetic biology designs to scale up in complexity, researchers will need to make greater use of specialized design tools and parts repositories. Seamless inter-tool communication would, for example, allow the separation of gene...

We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Even optimistic estimates suggest that most countries will likely take 6 to 24 months to vaccinate their citizens. These time estimates and the emergence of new viral strains urge us to find quick and effective ways to allocate the vaccines and contain the pandemic. While current approaches use combinations of age-based and occupation-based prioritizations, our strategy marks a departure from such largely aggregate vaccine allocation strategies. We propose a novel approach motivated by recent advances in (i) science of real-world networks that point to efficacy of certain vaccination strategies and (ii) digital technologies that improve our ability to estimate some of these structural properties. Using a realistic representation of a social contact network for the Commonwealth of Virginia, combined with accurate surveillance data on spatiotemporal cases and currently accepted models of within- and between-host disease dynamics, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals' degree (number of social contacts) and total social proximity time is significantly more effective than the currently used age-based allocation strategy in terms of number of infections, hospitalizations and deaths. Our results suggest that in just two months, by March 31, 2021, compared to age-based allocation, the proposed degree-based strategy can result in reducing an additional 56−110k infections, 3.2− 5.4k hospitalizations, and 700−900 deaths just in the Commonwealth of Virginia. Extrapolating these results for the entire US, this strategy can lead to 3−6 million fewer infections, 181−306k fewer hospitalizations, and 51−62k fewer deaths compared to age-based allocation. The overall strategy is robust even: (i) if the social contacts are not estimated correctly; (ii) if the vaccine efficacy is lower than expected or only a single dose is given; (iii) if there is a delay in vaccine production and deployment; and (iv) whether or not non-pharmaceutical interventions continue as vaccines are deployed. For reasons of implementability, we have used degree, which is a simple structural measure and can be easily estimated using several methods, including the digital technology available today. These results are significant, especially for resource-poor countries, where vaccines are less available, have lower efficacy, and are more slowly distributed.

One of the foundations of synthetic biology is the project to develop libraries of standardized genetic parts that could be assembled quickly and cheaply into large systems. The limitations of the initial BioBrick standard have prompted the development of multiple new standards proposing different avenues to overcome these shortcomings. The lack of compatibility between standards, the compliance of parts with only some of the standards or even the type of constructs that each standard supports have significantly increased the complexity of assembling constructs from standardized parts. Here, we describe computer tools to facilitate the rigorous description of part compositions in the context of a rapidly changing landscape of physical construction methods and standards. A context-free grammar has been developed to model the structure of constructs compliant with six popular assembly standards. Its implementation in GenoCAD makes it possible for users to quickly assemble from a rich library of genetic parts, constructs compliant with any of six existing standards.

ObjectivesThis research studies the role of slums in the spread and control of infectious diseases in the National Capital Territory of India, Delhi, using detailed social contact networks of its residents.MethodsWe use an agent-based model to study the spread of influenza in Delhi through person-to-person contact. Two different networks are used: one in which slum and non-slum regions are treated the same, and the other in which 298 slum zones are identified. In the second network, slum-specific demographics and activities are assigned to the individuals whose homes reside inside these zones. The main effects of integrating slums are that the network has more home-related contacts due to larger family sizes and more outside contacts due to more daily activities outside home. Various vaccination and social distancing interventions are applied to control the spread of influenza.ResultsSimulation-based results show that when slum attributes are ignored, the effectiveness of vaccination can be overestimated by 30%–55%, in terms of reducing the peak number of infections and the size of the epidemic, and in delaying the time to peak infection. The slum population sustains greater infection rates under all intervention scenarios in the network that treats slums differently. Vaccination strategy performs better than social distancing strategies in slums.ConclusionsUnique characteristics of slums play a significant role in the spread of infectious diseases. Modelling slums and estimating their impact on epidemics will help policy makers and regulators more accurately prioritise allocation of scarce medical resources and implement public health policies.